230 citations · 680 across the 32 of their papers we have counts for
35 papers
An Empirical Analysis of Static Analysis Methods for Detection and Mitigation of Code Library Hallucinations
Clarissa Miranda-Pena, Andrew Reeson, Cécile Paris +2
Despite extensive research, Large Language Models continue to hallucinate when generating code, particularly when using libraries. On NL-to-code benchmarks that require library use…
Simple and Effective Baselines for Code Summarisation Evaluation
Jade Robinson, Jonathan K. Kummerfeld
Code documentation is useful, but writing it is time-consuming. Different techniques for generating code summaries have emerged, but comparing them is difficult because human evalu…
Should I Trust You? Detecting Deception in Negotiations using Counterfactual RL
Wichayaporn Wongkamjan, Yanze Wang, Feng Gu +4
An increasingly common socio-technical problem is people being taken in by offers that sound ``too good to be true'', where persuasion and trust shape decision-making. This paper i…
Aligning AI Research with the Needs of Clinical Coding Workflows: Eight Recommendations Based on US Data Analysis and Critical Review
Yidong Gan, Maciej Rybinski, Ben Hachey +1
Clinical coding is crucial for healthcare billing and data analysis. Manual clinical coding is labour-intensive and error-prone, which has motivated research towards full automatio…
Personalized Help for Optimizing Low-Skilled Users' Strategy
Feng Gu, Wichayaporn Wongkamjan, Jonathan K. Kummerfeld +3
AIs can beat humans in game environments; however, how helpful those agents are to human remains understudied. We augment CICERO, a natural language agent that demonstrates superhu…
Do Text-to-Vis Benchmarks Test Real Use of Visualisations?
Hy Nguyen, Xuefei He, Andrew Reeson +3
Large language models are able to generate code for visualisations in response to simple user requests. This is a useful application and an appealing one for NLP research because p…